Development of an operational procedure to estimate surface albedo from the SEVIRI/MSG observing system in using POLDER BRDF measurements

Abstract

A statistical inversion method is first presented in support to the application of kernel-based BRDF (bi-directional reflectance distribution function) models for the calculation of the surface albedo. We present an operational procedure for the inversion of a kernel-driven BRDF model and further albedo retrieval to be applicable to the SEVIRI/MSG reflectance measurements. The processing steps applied to space-borne POLDER sensor data were as follows: (1) quality control, (2) accumulation of a priori information on model coefficients of directional hemispherical reflectance, (3) implementation of the BRDF model inversion methods based on the biased estimation instead of usual non-biased least solution, which has too big a variance in this case. The data control procedure consists both in filtering inputs of reflectance data and output of model coefficients based on analysis criteria determined by Fisher statistics. A multi-criteria procedure follows considering in particular the shape of the reflectance angular signature: (1) T-statistics, (2) the bowl shape index, (3) the dome shape index, (4) the white sky albedo (bi-hemispherical reflectance), (5) the black sky albedo variance (directional hemispherical reflectance). The procedure is applied to POLDER data corresponding to the 16 classes of IGBP land cover classification. The statistical results include mean values and covariance matrix for the spectral BRDF model coefficients.